Neural Markers of Auditory Symbol Learning: Multiscale EEG Evidence from Morse Code Training

Neural Markers of Auditory Symbol Learning: Multiscale EEG Evidence from Morse Code Training | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Neural Markers of Auditory Symbol Learning: Multiscale EEG Evidence from Morse Code Training Zhongyang He, Ying Zeng, Hua Zhao, Li Tong, Shan Gao, Yuanlong Gao, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9031528/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract To investigate how symbolic system learning induces neural plasticity, we examined the neural mechanisms of auditory symbolic processing using Morse Code (MC), a structured auditory symbolic system. In this study, novice learners underwent two months of MC training while electroencephalography (EEG) was recorded before and after training. We examined training-induced neural plasticity at two complementary levels: the local level and the global level. At the local level, MC training led to a significant decrease in N200 amplitude at the Fz electrode ( p < 0.05), indicating reduced engagement of controlled processing and a shift toward more automated processing during the dot-count discrimination task (i.e., more efficient early task processing). At the global level, phase-locking value (PLV) analyses revealed a training-associated reorganization of task-evoked functional connectivity, with the right temporal T8 node showing increased hub-like centrality and network properties becoming more favorable for information integration and transmission. These findings suggest that, as a result of training, the brain's perception of rhythmic auditory stimuli has changed, reflecting both local processing optimization and global network reorganization. The findings were consistent with training-associated changes in task-evoked neural dynamics at both event-related potentials (ERP) and network levels, captured by candidate neural markers integrating ERP and network metrics. Neural Markers Auditory Symbol Learning Morse Code EEG Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9031528","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":607366845,"identity":"0332e61a-64c8-4a3d-919b-ffb3efdcbc4d","order_by":0,"name":"Zhongyang He","email":"","orcid":"","institution":"Information Engineering University","correspondingAuthor":false,"prefix":"","firstName":"Zhongyang","middleName":"","lastName":"He","suffix":""},{"id":607366846,"identity":"ebe48f92-a315-429c-9b37-903d5741eea2","order_by":1,"name":"Ying Zeng","email":"","orcid":"","institution":"Information Engineering 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In this study, novice learners underwent two months of MC training while electroencephalography (EEG) was recorded before and after training. We examined training-induced neural plasticity at two complementary levels: the local level and the global level. At the local level, MC training led to a significant decrease in N200 amplitude at the Fz electrode (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), indicating reduced engagement of controlled processing and a shift toward more automated processing during the dot-count discrimination task (i.e., more efficient early task processing). At the global level, phase-locking value (PLV) analyses revealed a training-associated reorganization of task-evoked functional connectivity, with the right temporal T8 node showing increased hub-like centrality and network properties becoming more favorable for information integration and transmission. 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